3 ms·

Where previously it took 100 units of effort to deal with 10 units of effort of bullshit, it now takes 100 to deal with 1. This is only irrelevant if you place

Where previously it took 100 units of effort to deal with 10 units of effort of bullshit, it now takes 100 to deal with 1. This is only irrelevant if you place no value on the time of yourself and others.

cal85 3y ago
It’s a shame it’s now so much easier for bullshitters to produce bullshit quickly, but it is still irrelevant to whether a given piece of work is good or not.
- rscho 3y ago
  It's relevant because AI allows you to work faster and in larger volumes, and pushes quality down in the process. Because the user will optimize for quantity, not quality (which wouldn't be a viable choice in the absence of AI)
  - ghaff 3y ago
    If you don't think a lot of people don't already optimize for quantity, I have a bridge to sell you. I do get the point that LLMs make producing crap easier but that's somewhat independent of LLMs being used generally--which is going to happen in any case.
    - rscho 3y ago
      Honestly, I don't think it's viable to manually optimize for quantity in academic paper reviewing, specifically. But I might be wrong, of course. I think it's too much work for very little profit.
      - ghaff 3y ago
        I was speaking more generally. I'm not really in the "biz" but not sure what the incentives are to do a crap job of academic paper reviewing at scale.
        rscho 3y ago
        Basically, the only incentives are to slightly improve your resume by showing you are a reviewer for reputable journals, and to get fee waivers for publishing your own work in said journal (in crappy journals, usually). But you if you review a lot, you may get selected to be an editor and then climb the ladder from there, to be editor in a better journal, or become editor-in-chief, all of which can be prestigious (and paid) positions.
  - danaris 3y ago
    And even if further advances in ML can improve the "writing quality", overall quality is a much more multidimensional thing, and being able to produce a convincing-sounding review (formatted correctly, talks about actual content within the review, etc) is not the same as giving a useful one. As another comment in this subthread noted, if the author feels that an LLM-generated review is worthwhile, they can feed it to one themselves—and it's entirely possible that a specially-trained LLM could give some halfway decent reviews of some basic things like spelling and grammar, missing information or sections, that sort of thing, simply based on previous article drafts and their reviews. We should not be predicating our concerns about LLM-generated content solely on its "quality", because ultimately, the problem with it is that it is generic. I think it unlikely that it will have the ability to produce a genuine and thoughtful critique of a journal article until and unless there are significant breakthroughs, possibly even to the level of achieving AGI or something like it. Even using a more-advanced review-specific LLM like I describe above more widely does present serious concerns, because it runs the risk of suppressing articles that deviate from the "norm" in ways that the LLM doesn't have any way to appreciate, but which can present the findings better or even make the science better.
  - cal85 3y ago
    You seem to be arguing against some other point I have not made. I said it is irrelevant to whether a given piece of work is good or not. If a given piece of writing is good, it’s good regardless of what tools the writer used.
    - bryanrasmussen 3y ago
      If however a given piece of work is good but is produced with a tool that drives down the average quality of the field it may be reasonable to ask that people not use the tool, even if they produce good work with it
- hedora 3y ago
  This is an instance of the "99% accurate test says you have an incredibly rare disease" fallacy. As the percentage of garbage that goes into peer review (or any other filter) increases, the percentage of garbage that manages to sneak through will increase.
Erratic6576 3y ago
We just need some sort of AI which can help us filter through all the bullshit
burnished 3y ago
Different sort of relevancy. It is relevant that generating good looking bullshit became much faster and cheaper to the overall process because it means that assessing someone's contributions is more difficult, but it is not relevant when you're giving feedback on the hypothetically critical feedback you received in the first place. All that matters there is whether it was useful or not. Someone submitting AI generated reviews becomes relevant again when deciding whether to keep a reviewer around - a pattern of useful looking but useless and time wasting 'contributions' is relevant. Basically don't over index on whether someone is using AI to be a shitter, focus on the problematic behavior.

cal85 3y ago

It’s a shame it’s now so much easier for bullshitters to produce bullshit quickly, but it is still irrelevant to whether a given piece of work is good or not.

rscho 3y ago
It's relevant because AI allows you to work faster and in larger volumes, and pushes quality down in the process. Because the user will optimize for quantity, not quality (which wouldn't be a viable choice in the absence of AI)
- ghaff 3y ago
  If you don't think a lot of people don't already optimize for quantity, I have a bridge to sell you. I do get the point that LLMs make producing crap easier but that's somewhat independent of LLMs being used generally--which is going to happen in any case.
  - rscho 3y ago
    Honestly, I don't think it's viable to manually optimize for quantity in academic paper reviewing, specifically. But I might be wrong, of course. I think it's too much work for very little profit.
    - ghaff 3y ago
      I was speaking more generally. I'm not really in the "biz" but not sure what the incentives are to do a crap job of academic paper reviewing at scale.
      - rscho 3y ago
        Basically, the only incentives are to slightly improve your resume by showing you are a reviewer for reputable journals, and to get fee waivers for publishing your own work in said journal (in crappy journals, usually). But you if you review a lot, you may get selected to be an editor and then climb the ladder from there, to be editor in a better journal, or become editor-in-chief, all of which can be prestigious (and paid) positions.
- danaris 3y ago
  And even if further advances in ML can improve the "writing quality", overall quality is a much more multidimensional thing, and being able to produce a convincing-sounding review (formatted correctly, talks about actual content within the review, etc) is not the same as giving a useful one. As another comment in this subthread noted, if the author feels that an LLM-generated review is worthwhile, they can feed it to one themselves—and it's entirely possible that a specially-trained LLM could give some halfway decent reviews of some basic things like spelling and grammar, missing information or sections, that sort of thing, simply based on previous article drafts and their reviews. We should not be predicating our concerns about LLM-generated content solely on its "quality", because ultimately, the problem with it is that it is generic. I think it unlikely that it will have the ability to produce a genuine and thoughtful critique of a journal article until and unless there are significant breakthroughs, possibly even to the level of achieving AGI or something like it. Even using a more-advanced review-specific LLM like I describe above more widely does present serious concerns, because it runs the risk of suppressing articles that deviate from the "norm" in ways that the LLM doesn't have any way to appreciate, but which can present the findings better or even make the science better.
- cal85 3y ago
  You seem to be arguing against some other point I have not made. I said it is irrelevant to whether a given piece of work is good or not. If a given piece of writing is good, it’s good regardless of what tools the writer used.
  - bryanrasmussen 3y ago
    If however a given piece of work is good but is produced with a tool that drives down the average quality of the field it may be reasonable to ask that people not use the tool, even if they produce good work with it
hedora 3y ago
This is an instance of the "99% accurate test says you have an incredibly rare disease" fallacy. As the percentage of garbage that goes into peer review (or any other filter) increases, the percentage of garbage that manages to sneak through will increase.

Erratic6576 3y ago

We just need some sort of AI which can help us filter through all the bullshit

burnished 3y ago

Different sort of relevancy. It is relevant that generating good looking bullshit became much faster and cheaper to the overall process because it means that assessing someone's contributions is more difficult, but it is not relevant when you're giving feedback on the hypothetically critical feedback you received in the first place. All that matters there is whether it was useful or not. Someone submitting AI generated reviews becomes relevant again when deciding whether to keep a reviewer around - a pattern of useful looking but useless and time wasting 'contributions' is relevant. Basically don't over index on whether someone is using AI to be a shitter, focus on the problematic behavior.